The Intention-to-Treat Principle: A Primer for the Orthopaedic Surgeon

Randomization in clinical trials reduces bias. Its intent is to generate groups of patients that are comparable with each other before starting a study. As a result, both known and unknown patient factors that may affect the outcome under investigation are balanced between the treatment groups, minimizing the risk of differences between the two groups at the onset of the trial. This helps to ensure that differences in outcomes observed between the groups are the result of the intervention. Anything that compromises the balance of these factors may introduce bias into the results1,2. If an imbalance between the groups skews the results in favor of one intervention over the other, this can lead to a biased study. Therefore, a randomized, double-blinded, placebo-controlled (when appropriate) trial with intention-to-treat analysis is considered to be the highest level of evidence in clinical research. This provides the clearest insight into the effect of the intervention being studied by controlling for as many factors as possible. Intention-to-treat analysis compares study groups in terms of the treatment to which they were randomly allocated, irrespective of the treatment they actually received2-4. If subjects do not receive the treatment to which they were originally randomized, they are in violation of the study protocol. There are several examples of protocol violation, including crossover from one treatment group to another, patients lost to follow-up, and inclusion of patients who should not have been included. Regardless of protocol violation, intention-to-treat analysis is done according to the originally assigned treatment groups because this helps to preserve the value of randomization. Some investigators exclude from analysis any participants who violate the study protocol (e.g., those who cross over, are lost to follow-up, or have insufficient follow-up). This is known as per-protocol analysis2. Patients …